Should we build our AI capability in-house or buy it?

Buying a tool gives you access, not capability — the seats don't teach your team to run agents in production. Building it alone works but burns senior quarters on a problem that isn't your product. For most teams the honest answer is neither pure build nor pure buy: bring in people who've done it to install the capability on your stack and standards, and transfer it so your team owns it without depending on a vendor.

0106why buying a tool isn't capability

Why buying a tool isn't capability

A license gives your team model access. None of what makes agents work in production (context, orchestration, observability, the operating model) comes in the box. You can own every seat and still be stuck at autocomplete.

0206why building it solo is expensive

Why building it solo is expensive

You can build the capability in-house, but it costs your best engineers a few quarters learning a problem space that isn't your product. Sometimes that's right; often it's the slowest path to a capability someone can install faster.

0306the third option: transfer

The third option: transfer

Bring in operators who've shipped this, have them build it on your environment and standards, and transfer it to your team. The win is your team's independence — capability that stays after the engagement, not a dependency.

0406common questions

Straight answers.

Isn't hiring senior AI engineers the build path?: It's one version of it, and a slow, expensive one given the market. Transfer gets you the capability faster and leaves your existing team able to run it.
Won't a consultant just create a dependency?: That's the bad version. A good engagement is measured by your independence (your team running agents without us), not by a retainer.
When does pure build make sense?: When the capability is core IP you want to own end to end and you have senior time to spend. For most teams it isn't, and transfer is faster.